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Advances in Epidemiological and Statistical Methods for Clinical Research

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Clinical Research Methods".

Deadline for manuscript submissions: closed (31 January 2025) | Viewed by 1591

Special Issue Editors


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Guest Editor
1. Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072 Milan, Italy
2. IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, 20089 Milan, Italy
Interests: biostatistics; clinical research methodology; epidemiology; evidence based medicine; evidence synthesis; medical statistics; meta-analysis; systematic reviews
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
1. Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072 Milan, Italy
2. IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, 20089 Milan, Italy
Interests: biostatistics; prediction modelling; evidence synthesis; clinical research methodology; epidemiology; evidence based medicine
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Our Special Issue, entitled “Advances in Epidemiological and Statistical Methods for Clinical Research”, will focus on presenting the latest advancements in epidemiological and statistical methodologies tailored for clinical research. We encourage all authors to submit articles related to a wide range of methodologies, including novel study designs, advanced statistical techniques, causal inference methods, meta-analysis and systematic review methods, strategies for addressing bias and confounding in observational studies, the development and validation of prediction models, and methodological challenges and solutions in specific areas of clinical research. Articles will be considered for publication in this Special Issue only if they are relevant to our clinical research. Contributions will be part of an ongoing dialogue on methodological advances in clinical research and facilitate the translation of research findings into improved outcomes for patients.

Dr. Stefanos Bonovas
Dr. Daniele Piovani
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • epidemiology
  • biostatistics
  • clinical research
  • statistical methodologies
  • causal inference
  • meta-analysis
  • observational studies
  • prediction models
  • study designs
  • data analysis
  • bias and confounding
  • evidence-based medicine

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Published Papers (1 paper)

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Research

14 pages, 496 KiB  
Article
Validation of Psychometric Properties of Partners in Health Scale for Heart Failure
by Pupalan Iyngkaran, David Smith, Craig McLachlan, Malcolm Battersby, Maximilian De Courten and Fahad Hanna
J. Clin. Med. 2024, 13(23), 7374; https://doi.org/10.3390/jcm13237374 - 3 Dec 2024
Cited by 1 | Viewed by 1103
Abstract
Background: Congestive heart failure (CHF) is a complex chronic disease, and it is associated with a second comorbid condition in more than half of cases. Self-management programs can be specific to CHF or generic for chronic diseases. Several tools have been validated for [...] Read more.
Background: Congestive heart failure (CHF) is a complex chronic disease, and it is associated with a second comorbid condition in more than half of cases. Self-management programs can be specific to CHF or generic for chronic diseases. Several tools have been validated for CHF. Presently, there are no established generic instruments that are validated for measuring self-management in CHF. Objective: This study aims to evaluate the internal reliability and construct validity (psychometric properties) of the Partners in Health (PIH) scale for patients with congestive heart failure, a generic chronic disease self-management tool. Methods: The study included 210 adult CHF patients [120 with heart failure with reduced ejection fraction (HfrEF), 90 with preserved ejection fraction (HfpEF)], from Community Cardiology Outpatients in West Melbourne, Australia, who were treated in community cardiology and were included between May 2022 and Jan 2024. The screened patient population were diagnosed with CHF and were eligible for an SGLT-2 inhibitor. Cohort analysis used the Bayesian confirmatory factor analysis to evaluate the a priori four-factor structure. Omega coefficients and 95% credible intervals (CI) were used to assess internal reliability. Results: In the CHF (HFrEF) and preserved ejection fraction (HFpEF) cohorts, participants’ mean [standard deviation (SD)] age was 66.8 (13.5) and 71.3 (9.76) years. Description of study sociodemographics highlighted that 88% and 52% of patients were male, there was a BMI > 50% in both cohorts, eGFR > 60 mL/min were 59% and 74%, and LVEF < 40% and > 50% were 99% and 100%, respectively. Model fit for the hypothesised model was adequate (posterior predictive p = 0.073) and all hypothesised factor loadings were substantial (>0.6) and significant (p < 0.001). Omega coefficients (95% CI) for the PIH subscales of Knowledge, Partnership, Management and Coping were 0.84 (0.79–0.88), 0.79 (0.73–0.84), 0.89 (0.85–0.91) and 0.84 (0.79–0.88), respectively. Conclusion: This study is original in confirming the dimensionality, known-group validity, and reliability of the PIH scale for measuring generic self-management in outpatients with CHF syndrome. Full article
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